Understanding key habitat requirements is critical to the conservation of species at risk. For highly mobile species, discerning what is key habitat as opposed to areas that are simply being traversed (perhaps in the search for key habitats) can be challenging. For seabirds, in particular, it can be difficult to know which areas in the sea represent key foraging grounds. Devices that record birds’ diving behaviour can help shed light on this, but they’re expensive to deploy. In contrast, devices that record the birds’ geographic position are more commonly available and have been around for some time.

In their recent study entitled ‘Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds,’ Ella Browning and her colleagues made use of a rich dataset on 399 individual birds from three species, some equipped with both global positioning (GPS) and depth recorder devices, others with GPS only. The data allowed them to test whether deep learning methods can identify when the birds are diving (foraging) based on GPS data alone. Results were highly promising, with top models able to distinguish non-diving and diving behaviours with 94% and 80% accuracy. Continue reading →

Digital photography has revolutionised the way we view ourselves, each other and our environment. The use of automated cameras (including camera traps) in particular has provided remarkable opportunities for biological research. Although mostly used for recreational purposes, the development of user-friendly, versatile auto-focus digital single lens reflex (DSLR) cameras allows researchers to collect large numbers of high quality images at relatively little cost.

DNA dietary analysis is a non-invasive tool used to identify the food consumed by vertebrates. The method relies on identifying prey DNA in the target animals’ scats. It’s especially useful for marine animals such as seals and seabirds as it is difficult to watch their feeding events.

Cameras and wildlife monitoring

Behavioural and ecological research and monitoring of wildlife populations are based on collection of field data. Demographic data, such as breeding frequency, birth rates and juvenile survival, have been critical in understanding population trends for a wide range of species.

Photography has been extensively used by field biologists and ecologists to gather these data and they have been quick to take up improvements in this technology. Many field programmes today use photography either for primary data collection or the communication of results. Advances in digital photography, image storage and transmission, image processing software and web-based dissemination of images have been extremely rapid in recent years, offering ecologists and biologists a range of powerful tools.

Digital imagery has been captured from a wide range of platforms, each of which has various advantages and limitations for biological study. The most remote images are captured from satellite-based sensors, which have been used to assess population abundance of large animals, such as elephant seals, or locate colonies of emperor penguins. Cameras mounted on aircraft can also provide large-scale perspectives but both of these platforms suffer from high cost, operational limitations due to weather, and limited temporal replication. Recent use of drones, while cheaper, still requires a person to be close to the survey location and can only be used in short bursts, typically lasting less than 20 minutes.

Land-based cameras – or those fixed onto animals – can track behaviour closely, but have low sample size as data tends to be collected at the scale of individual or small groups. To improve replication, fleets of remote cameras can be used or multiple images stitched together post hoc to form a montage. However, this increases cost, either for hardware or labour to manually construct panoramas. To date all these camera systems have had limits to their spatial and/or temporal resolution and, therefore, to the number of individuals covered. This restricts biological study at the population level. Continue reading →

This month’s issue contains two Applications articles and one Open Access article, all of which are freely available.

– letsR: A package for the R statistical computing environment, designed to handle and analyse macroecological data such as species’ geographic distributions and environmental variables. It also includes functions to obtain data on species’ habitat use, description year and current as well as temporal trends in conservation status.

– Cleaning Oil from Seabirds: The authors assess the efficacy of sea water as an alternative to fresh water for cleaning oil from seabirds’ feathers. Results indicate that for oiled feathers, a sea water wash/rinse produced clean, low BAI/unclumped feathers with minimal particulate residue.

Stefano Canessa et al. provide this month’s only Open Access article. In ‘When do we need more data? A primer on calculating the value of information for applied ecologists‘ the authors guide readers through the calculation of Value of Information (VoI) using two case studies and illustrate the use of Bayesian updating to incorporate new information. Collecting information can require significant investments of resources; VoI analysis assists managers in deciding whether these investments are justified. The authors also wrote a blog post on VoI which you can find here.

Today is 10th National Wildlife Day. As we have done for a few awareness days this year (Bats, Biodiversity and Bees so far) we are marking the day by highlighting some of our favourite Methodsin Ecology and Evolution articles on the subject. Obviously ‘wildlife’ is a pretty big topic, so we have narrowed our focus (slightly) to monitoring wildlife (with one or two additional papers that we didn’t want to leave out).

This list is certainly not exhaustive and there are many more wonderful articles on these topics in the journal. You can see more of them on the Wiley Online Library.